View
213
Download
0
Category
Tags:
Preview:
Citation preview
http://cal044202.student.utwente.nl/~johan/butterfl/europe/uppsala/uppsalanight.jpg
InvitedInvitedTalkTalk
Amit Sheth, Vipul Kashyap Amit Sheth, Vipul Kashyap andand Tarcisio Lima Tarcisio Lima
Large-Scale Distributed Information Systems Lab.Large-Scale Distributed Information Systems Lab.
University of Georgia, Athens, GA USAUniversity of Georgia, Athens, GA USA
http://lsdis.cs.uga.eduhttp://lsdis.cs.uga.edu July 31 August 2
Uppsala Sweden
3th International Workshop on
Cooperative Information AgentsCIA'99
TraditionalEnvironment
ComputerAssisted
Environment
Challenging Application:Challenging Application:
learning and manipulating learning and manipulating
concepts on the Webconcepts on the Web
We should explore richer and much more complex new information requests
perspective Iperspective I
State-of-the-artState-of-the-art
How are we learning on the Web?How are we learning on the Web?
How are we learning on the Web?How are we learning on the Web?
perspective IIperspective IICurrent issues: searchCurrent issues: search
Browsing, classificationQuerying
keyword: ubiquitousattribute: on very limited set of metadatacontent: almost none
BLENDED BROWSING & QUERYING INTERFACEBLENDED BROWSING & QUERYING INTERFACE
SEMANTIC BROWSINGSEMANTIC BROWSING
ATTRIBUTE & KEYWORDQUERYING
ATTRIBUTE & KEYWORDQUERYING
uniform view of worldwide distributed assets of similar type
Targeted e-shopping/e-commerce
assets access
How are we taking advantage of the Web?How are we taking advantage of the Web?
How are we taking advantage of the Web?How are we taking advantage of the Web?
VideoAnywhereVideoAnywhere™™ Backend Architecture
VideoAnywhere is a trademark of UGARF, Inc.
Video Content Agent
METABASEMETABASEwith
user profiles
APIAPI UserAgent
ExtractorOntology
Table
ExtractorOntology
Table
EPGextractor agent
EPGextractor agent
EPG
VideoDomeextractor agent
VideoDomeextractor agent
FoxNewsextractor agent
FoxNewsextractor agent
VideoDome FoxNews
Black Boxextractor agent
Black Boxextractor agent
“bachelor’sparty”T
VW
eb
open sourcecontent open source and partner content original content
check/extract
check/extract
check/extract
check/extract
XML XMLXML XML
insertclean upthreadtranslate
tags
user query &browsingprofiling
daily topten assetspush
pullMETABASEMETABASEwith
user profiles
APIAPI
MermaidMermaidDDTSDDTS
Multibase, MRDSM, ADDS, Multibase, MRDSM, ADDS, IISS, Omnibase, ...IISS, Omnibase, ...
Generation IGeneration I
1980s1980s
Evolving targets and approaches in integratingEvolving targets and approaches in integratingdata and information data and information (a personal perspective)(a personal perspective)
DL-II projectsDL-II projectsADEPT,ADEPT,InfoQuiltInfoQuilt
Generation IIIGeneration III
1997...1997...
InfoSleuth, KMed, DL-I projectsInfoSleuth, KMed, DL-I projectsInfoscopes, HERMES, SIMS, Infoscopes, HERMES, SIMS,
Garlic,TSIMMIS,Harvest, RUFUS,... Garlic,TSIMMIS,Harvest, RUFUS,...
Generation IIGeneration II
1990s1990s
VisualHarnessVisualHarnessInfoHarnessInfoHarness
a society for ubiquitous exchange of (tradeable) information in all digital forms of representation;
information anywhere, anytime, any forms
perspective IIIperspective III
Looking ahead:Looking ahead:
Supporting information brokering (for decision making and learning) is much more than current e-commerce
involving products and services
A minimal definition on the Global Information Infrastructure
Information brokering is an architecture that
guides creation and management of
information systems and semantic-level
solutions to serve a variety of information
stakeholders (participants), including
providers, facilitators, consumers, and the
business involved in creating, enhancing
and using of information.
Semantic Information Brokering Semantic Information Brokering IntroductionIntroduction
How should we learn?How should we learn? (an example scenario)(an example scenario)
Graduate students in a College of Geography have a final
project in which a case of study is proposed. In the case, they
are supposed to help a City Council in making decisions over
the planning of a new landfill. This is a hands-on learning
exercise through the interaction
with a Digital EarthDigital Earth and the start
point would be to find the best
location for the landfill*.
Tacoma Landfill
* This scenario comes in support of one of the suggestions for
Digital Earth scenarios sampled by the “First Inter-Agency Digital
Earth Working Group, an effort on behalf of NASA’s inter-agency
Digital Earth Program.
How should we learn?How should we learn? (an example scenario)(an example scenario)
bydefinition
bysemantics by
synonymy A first cut refinement leads us to the following information request:
FindFind a proper soil in sites not subject to flooding or high a proper soil in sites not subject to flooding or high
groundwater levelsgroundwater levels for a new landfill nearnear thethe industrial zone industrial zone.
Liquefaction phenomenon cannot occurLiquefaction phenomenon cannot occur.
Find a landfill sitelandfill site for a new landfill near the source of the wastessource of the wastes.
The earthquakes’ impacts must be evaluatedThe earthquakes’ impacts must be evaluated..
A high level information request would be:
How should we learn?How should we learn? (an example scenario)(an example scenario)
Adding on-the-fly user constraints while processing the information request:
Retrieve satellite images in 12-meter resolution or higher,Retrieve satellite images in 12-meter resolution or higher,
looking for soils with permeability rate < 10 looking for soils with permeability rate < 10 (silty clay loam)
for a new landfill
whose distance from the city industrial park is less than 5km.whose distance from the city industrial park is less than 5km.
Using the images’ coordinates, forecast seismic activity up to Using the images’ coordinates, forecast seismic activity up to
moderate magnitude moderate magnitude (5 - 5.9, Richter scale) in the pointed areas. in the pointed areas.
domain specific metadata; correlation among multiple ontologies; return results in multiple media (in this case, images and a simulation)
How should we learn?How should we learn? (an example scenario)(an example scenario)
Partial sample ontologies for semantic information brokering:
LANDUSE
COMERCIAL
INDUSTRIAL
RURAL
RESIDENTIAL
AGRICULTURAL
MILITARYRECREATIONAL
LAND(SITE)
CULTIVATEDAREA
GREENLANDAREA LAND
BANK
ZONING
LANDFILLSITE
WASTEDISPOSAL
RECYCLING
HAZARDOUS
LANDFILLRESOURCE REC.
SOLID SEWAGE
shredding
magneticseparation
screening
washing
NATURALDISASTER
EARTHQUAKE
causes
LANDSLIDE
VOLCANO
STORMFLOOD
FIRE
AVALANCHE
TSUNAMI
causes
causes
causes
How should we learn?How should we learn? (an example scenario)(an example scenario)
A sample result (depending on information providers) could be:
OrbView-4’s stereo imaging capacity providing 3-D terrain images
Hyperspectral data will be valuable for identifying material types
images source: http://www.orbimage.com
5km
industrial zoneindustrial zone
identified landfill siteidentified landfill site
The students now have the information requested for
helping the City Council in the planning of the new landfill
Semantic Information Brokering Semantic Information Brokering IntroductionIntroduction
INFORMATION HETEROGENEITY
Semantic Heterogeneity
Structural, Representational/Schematic Heterogeneity
Syntactic, Format Heterogeneity
SYSTEM HETEROGENEITY
Information System HeterogeneityDigital Media Repository Management Systems
Database Management Systems, (heterogeneity
of DBMSs, data models, system capabilities such
as concurrency control and recovery)
Platform HeterogeneityOperating System (heterogeneity of file system, naming, file types, operation, transaction support, IPC)
Hardware/System (heterogeneity of instruction set, data representation/coding)
Semantic InteroperabilitySemantic Interoperability
Structural InteroperabilityStructural Interoperability
Syntactic InteroperabilitySyntactic Interoperability
System InteroperabilitySystem Interoperability
A taxonomy for heterogeneity and interoperabilityA taxonomy for heterogeneity and interoperability
Impacts on Information OverloadImpacts on Information Overload
Heterogeneity:
differences in structure;
differences in query languages;
semi-structured or unstructured data;
media heterogeneity;
terminology (and language) heterogeneity;
contextual heterogeneity
Heterogeneity...Heterogeneity... … … is a Babel Tower!!is a Babel Tower!!
SEMANTIC INTEROPERABILITYSEMANTIC INTEROPERABILITY
metadata
ontologies
contexts
SEMANTIC HETEROGENEITYSEMANTIC HETEROGENEITY
Impacts on Information OverloadImpacts on Information Overload
Globalization: challenge of the scale
information resource discovery;
modeling of information content;
querying of information content
information focusing
information correlation
Much more than returning documents with potentially relevant information.
Handling the information overloadHandling the information overload
S E M A N T I S E M A N T I C S C S
S T R U C T U R ES T R U C T U R E
S Y N T A XS Y N T A X
S Y S T E MS Y S T E M
C O N S U M E R SC O N S U M E R S
F A C I L I T A T O R SF A C I L I T A T O R S
P R O V I D E R SP R O V I D E R SD
A T
AD
A T
A
M E
T A
D A
T A
M E
T A
D A
T A
T E
R M
I N O
L O
G Y
T E
R M
I N O
L O
G Y
Stakeholders and beneficiaries in information brokering
Handling the information overloadHandling the information overload
S E M A N T I S E M A N T I C S C S
S T R U C T U R ES T R U C T U R E
S Y N T A XS Y N T A X
S Y S T E MS Y S T E M
C O N S U M E R SC O N S U M E R S
F A C I L I T A T O R SF A C I L I T A T O R S
P R O V I D E R SP R O V I D E R SD
A T
AD
A T
A
M E
T A
D A
T A
M E
T A
D A
T A
T E
R M
I N O
L O
G Y
T E
R M
I N O
L O
G Y
Stakeholders and beneficiaries in information brokering
key player on the GII, who help to match key player on the GII, who help to match
the consumersthe consumers REQUESTS REQUESTS with the with the
INFORMATIONINFORMATION exported by the providers exported by the providers
F A C I L I T A T O R SF A C I L I T A T O R S
C O N S U M E R SC O N S U M E R S
key player on the GII, key player on the GII,
which which USEUSE information informationkey player on the GII, key player on the GII,
which which EXPORTEXPORT information information
P R O V I D E R SP R O V I D E R S
Handling the information overloadHandling the information overload
Information facilitatorsInformation facilitators enable brokeringbrokering between the information consumer and provider that may be defined as:
arbitration between consumers and providers for resolving the
information impedance, the differing worldviews of the
consumers and providers;
dynamic re-interpretation of information requests for
determination of relevant information services and products;
dynamic creation and composition of information products
after suitable assembly or correlation of information
components available from the various providers, or other
value addition activities.
INFORMATION/DATAINFORMATION/DATAOVERLOADOVERLOAD
INFORMATION PROVIDERS
InformationSystem
DataRepository
InformationSystem
INFORMATION CONSUMERS
User Query
User Query
User Query
INFORMATION BROKERINGINFORMATION BROKERING
InformationSystem
DataRepository
InformationSystem
InformationRequest
InformationRequest
InformationRequest
Corporations
Universities
People
Government
Programs
Newswires
Universities
Corporations
Research Labs
Handling the information overload
information brokering stakeholder perspective
Handling the information overloadHandling the information overload
S E M A N T I S E M A N T I C S C S
S T R U C T U R ES T R U C T U R E
S Y N T A XS Y N T A X
S Y S T E MS Y S T E M
C O N S U M E R SC O N S U M E R S
F A C I L I T A T O R SF A C I L I T A T O R S
P R O V I D E R SP R O V I D E R SD
A T
AD
A T
A
M E
T A
D A
T A
M E
T A
D A
T A
T E
R M
I N O
L O
G Y
T E
R M
I N O
L O
G Y
Levels of information brokeringLevels of information brokering
data brokering standards-based interoperabilitydata brokering standards-based interoperability
metadata-based brokeringmetadata-based brokering
semantic information brokeringsemantic information brokering
Handling the information overloadHandling the information overload
The role of facilitators on the GII:
design and construction of multimedia views using metadata
descriptions from standardized terminologies available to the
consumers;
maintenance and storage of associations between the digital
data exported by the providers and the metadata descriptions
designed by it;
bridge between providers and consumers
use of domain specific ontologiesdomain specific ontologies to characterize
vocabularies and terminological relationships in the
interoperation, reducing information overload
Handling the information overloadHandling the information overload
Services the facilitators can offer:
provide a collection of standard terminologies captured as
domain specific ontologies to the consumers, used by the
providers to construct metadata descriptions;
support the interoperation across multiple domain specific
ontologies;
support the transformation of information requests across
different ontologies, minimizing the loss of information.
key objective of the approach: enable semantic interoperability,
reducing the problem of knowing the structure and semantics
of data in the huge number of information sources.
Appropriateness of multi-agent systemsAppropriateness of multi-agent systems
Extensions to agent functionalities to support semantic information brokering:
capture, view and interrogate the semantics of the underlying
(multimedia) data;
request information without regards to the underlying data
type, structure, format or media in which the information may
be represented or stored;
support interoperation across multiple standard terminologies
or domain specific ontologies.
Demonstration Scenarios Demonstration Scenarios VOLCANOES ACTIVITYVOLCANOES ACTIVITY
Some volcanoes are more active than others, and a few
are in a state of permanent eruption, at least for the
geological present. Volcanoes may become quiescent
(dormant) for months or years. The danger to life posed by
active volcanoes is not limited to eruption of molten rock or
showers of ash and cinders.
Mudflows that melt ice and
snow on the volcano's flanks
are equally hazardous*.
* Encarta® 98 Desk Encyclopedia © & 1996-97 Microsoft Corporation.All rights reserved. Pu'u'O'o, Hawaii
Demonstration Scenarios Demonstration Scenarios VOLCANOES ACTIVITYVOLCANOES ACTIVITY
A sample information request:
Find information on volcanoesvolcanoes and also find how
these volcanoes affect/cause landslidesaffect/cause landslides and tsunamistsunamis.
Some of the ontologies involved in processing this information request are:
• Ontology for GIS Datasets;
• Ontology for Natural Disasters;
• Ontology for Volcanoes;
• Ontology for Landslides;
• Ontology for Tsunamis.
TRY HERE THIS AND OTHER CONCEPT DEMOS
Agents for media independent correlationsAgents for media independent correlations
UCSB’s Institute for CrustalStudies Earthquake Collection
Seismicity(SQL):
USGS GlobalLand Info System
Land(SQL)
NASA’s EOS EarthImages and Data
Image Features(IP routines)
ProviderAgent
ProviderAgent
ProviderAgent
CorrelationAgent
MetadataAgent
ConsumerAgent
Satelliteimage:
Seismicforecast:
Landfill site:
Objects displaying
USER INTERFACE
metadata extraction
metadataexportation
informationrequests
GUI construction
user constraints
metadata constraints
FINAL ANSWER (objects satisfying constraints)
control strategy
metadata extraction
metadata extraction
Information content
Agents for inter-ontology interoperationAgents for inter-ontology interoperation
ReformulationAgent
IntegrationAgent
OntologyAgent
ConsumerAgent
OntologyAgent
Ontology Aaerial-videography
Ontology Bland use classification
InformationRequest
ReformulatedRequest
InformationRequest
Ontology AB
INTEGRATION
Integrating aerial-videography with the
process of land use classification
is identified as an exciting example of
SEMANTIC INFORMATION BROKERINGSEMANTIC INFORMATION BROKERING,
leading to the gathering of ground-truth
satellite image interpretation and
post-classification land-cover mappings
In our starting example scenario:
Summary Summary
TextTextStructured DatabasesStructured Databases DataData Syntax,Syntax,
SystemSystem Federated DBFederated DB
Semi-structuredSemi-structured MetadataMetadata Structural,Structural,SchematicSchematic
Mediator,Mediator,Federated ISFederated IS
Visual,Visual,Scientific/Eng.Scientific/Eng. KnowledgeKnowledge SemanticSemantic
Knowledge Mgmt.,Knowledge Mgmt.,InformationInformationBrokering,Brokering,
Cooperative ISCooperative IS
ConclusionsConclusions
amit@cs.uga.edu - http://lsdis.cs.uga.edu
From Procedures, Objects, Components to Agentswe have a nice abstraction of computation.Now let’s apply them to address semantic-level issues
Information Brokering gives a framework for enabling
complex decision making and learning involving
heterogeneous digital media on the GII.
Recommended